Development of air quality measurement system using raspberry Pi

Air pollution is a major health issue in many countries. Air pollutants pose a danger to human health if their concentrations exceeding the tolerable levels. Monitoring such pollutants and their levels is an important precautionary measure to alarm the public about air quality around them. In Malays...

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Bibliographic Details
Main Authors: Mohd Pu'ad, Muhamad Farhan, Gunawan, Teddy Surya, Kartiwi, Mira, Janin, Zuriati
Format: Conference or Workshop Item
Language:English
English
Published: Institute of Electrical and Electronics Engineers Inc. 2018
Subjects:
Online Access:http://irep.iium.edu.my/71847/1/71847_Development%20of%20Air%20Quality%20Measurement.pdf
http://irep.iium.edu.my/71847/7/71847%20Development%20of%20Air%20Quality%20Measurement%20System%20using%20Raspberry%20Pi%20SCOPUS.pdf
http://irep.iium.edu.my/71847/
https://ieeexplore.ieee.org/document/8688748
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Summary:Air pollution is a major health issue in many countries. Air pollutants pose a danger to human health if their concentrations exceeding the tolerable levels. Monitoring such pollutants and their levels is an important precautionary measure to alarm the public about air quality around them. In Malaysia, the Department of Environment monitors air quality using costly continuous air quality monitoring stations (CAQMs) installed at fixed locations of highly populated and industrial areas. For other areas, their API readings are just estimates taken from the nearest CAQMs. Furthermore, most of the CAQMs still do not measure particulate matters (PM) smaller than 2.5 micron (PM2.5). The objective of this paper is to develop an air quality measurement system which can measure PM smaller than 10 and 2.5 microns, and four hazardous gasses, including carbon monoxide, sulphur dioxide, ground level ozone and nitrogen dioxide. The functionality of the system was evaluated by measuring sub-API readings in areas with low and high traffic volumes. Experimental results showed that the proposed system was highly responsive and able to detect the types and concentrations of pollutants instantly. For validation, the device API readings was compared with API of the nearby Batu Muda CAQMS, in which 3.23% error was obtained.